Many sources for current weather and traffic information are available to drivers for use in planning routes to avoid congestion or other delays. However, drivers may not remember to consider possible delays until a journey is underway. Planning in advance may help mitigate delays, but compiling available traffic and weather information can be a complicated task. Additionally, predicted traffic or weather situations may change prior to a planned departure thereby reducing the usefulness of advanced planning.
Another consideration is the time and effort involved in detailed route planning. Drivers do not typically have an entire afternoon to track traffic patterns, track weather fronts and modify planned routes to a destination. Drivers may not even be able to find and/or access all the resources needed to plan routes in this manner. If drivers can access all of these resources, it is a fairly unrealistic proposition to expect that people will spend a few hours each day planning the optimal version of a twenty or thirty minute commute.
A few decades ago, a driver would access a paper map, determine a route to a destination, and utilize any local knowledge and weather reports to optimize the route, if possible. Changes in weather and traffic encountered along the route would simply be accommodated in stride. Nowadays, navigation systems can help identify routes, road closures and traffic backups. But traffic has a historic component and is also subject to instantaneous changes. Similarly, weather reports are somewhat unreliable and their projected effect on a route may vary as a day progresses and weather patterns change. While there is a great deal more information available to optimize routes, the disconnected and dynamic nature of the data presents new problems with respect to access and effect-determination, respectively.